Name: Mangaliso Samuel Makhoba
Type: User
Bio: BSc Computational and Applied Mathematics (University Of The Witwatersrand (Wits))
Postgraduate Certificate In Education (Wits)
Data Scientist
Location: Johannesburg, South Africa
Mangaliso Samuel Makhoba's Projects
Template repository for the EDSA Classification Predict
This project makes graphical exploratory data analysis of the Corona Virus from a South African database created and updated by Explore Data Science Academy in partnership with the South African Government
Using Decision Tree Regression to predict world population
Extracting data from twitter, Transforming it in Python, Loading it in SQL. Please refer to Readme.md for more details
In this challenge, we train the model with images of hand drawn numbers with their respective labels. Then use the classifier to predict the label given the image in pixels. Refer to README.md for more details
In this project, we use Ridge Regression Model to predict the population of a certain country at a particular year having trained the data with the world population from 1960 to 2017
This is an introductory use of Logistic Regression into solving classification problems. Refer to to README.md for more details
Natural Language Processing Classifcation Project analyzing Tweets for sentiment analysis
This project is using the Wine Quality Data Set to create a model that will predict the wine quality based on physicochemical tests, after tuning the hyperparameters. Refer to Readme.md for more details
Using Random Forest Regression to predict world population. Refer to README.me for more details
Template repository used for creating a simple regression-based API
The focus of this project is the building of functions for Eskom to preprocess Data from Eskom, and prepare it for Sentiment Analysis. Refer to README.md for more details
Exploratory Data Analysis on the raw data from the Titanic Kaggle Challenge. The purpose of this challenge is to predict the probability of survival for a given passenger, given their boarding details.
Simple statistical prediction of the survival chances of the passengers in the testing set, given certain conditions as input. Refer to README.md for more detail
Sendy Logistics Zindi Competition